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VESPUCCI: Exploring Patterns of Gene Expression in Grapevine

Large-scale transcriptional studies aim to decipher the dynamic cellular responses to a stimulus, like different environmental conditions. In the era of high-throughput omics biology, the most used technologies for these purposes are microarray and RNA-Seq, whose data are usually required to be depo...

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Autores principales: Moretto, Marco, Sonego, Paolo, Pilati, Stefania, Malacarne, Giulia, Costantini, Laura, Grzeskowiak, Lukasz, Bagagli, Giorgia, Grando, Maria Stella, Moser, Claudio, Engelen, Kristof
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4862315/
https://www.ncbi.nlm.nih.gov/pubmed/27242836
http://dx.doi.org/10.3389/fpls.2016.00633
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author Moretto, Marco
Sonego, Paolo
Pilati, Stefania
Malacarne, Giulia
Costantini, Laura
Grzeskowiak, Lukasz
Bagagli, Giorgia
Grando, Maria Stella
Moser, Claudio
Engelen, Kristof
author_facet Moretto, Marco
Sonego, Paolo
Pilati, Stefania
Malacarne, Giulia
Costantini, Laura
Grzeskowiak, Lukasz
Bagagli, Giorgia
Grando, Maria Stella
Moser, Claudio
Engelen, Kristof
author_sort Moretto, Marco
collection PubMed
description Large-scale transcriptional studies aim to decipher the dynamic cellular responses to a stimulus, like different environmental conditions. In the era of high-throughput omics biology, the most used technologies for these purposes are microarray and RNA-Seq, whose data are usually required to be deposited in public repositories upon publication. Such repositories have the enormous potential to provide a comprehensive view of how different experimental conditions lead to expression changes, by comparing gene expression across all possible measured conditions. Unfortunately, this task is greatly impaired by differences among experimental platforms that make direct comparisons difficult. In this paper, we present the Vitis Expression Studies Platform Using COLOMBOS Compendia Instances (VESPUCCI), a gene expression compendium for grapevine which was built by adapting an approach originally developed for bacteria, and show how it can be used to investigate complex gene expression patterns. We integrated nearly all publicly available microarray and RNA-Seq expression data: 1608 gene expression samples from 10 different technological platforms. Each sample has been manually annotated using a controlled vocabulary developed ad hoc to ensure both human readability and computational tractability. Expression data in the compendium can be visually explored using several tools provided by the web interface or can be programmatically accessed using the REST interface. VESPUCCI is freely accessible at http://vespucci.colombos.fmach.it.
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spelling pubmed-48623152016-05-30 VESPUCCI: Exploring Patterns of Gene Expression in Grapevine Moretto, Marco Sonego, Paolo Pilati, Stefania Malacarne, Giulia Costantini, Laura Grzeskowiak, Lukasz Bagagli, Giorgia Grando, Maria Stella Moser, Claudio Engelen, Kristof Front Plant Sci Plant Science Large-scale transcriptional studies aim to decipher the dynamic cellular responses to a stimulus, like different environmental conditions. In the era of high-throughput omics biology, the most used technologies for these purposes are microarray and RNA-Seq, whose data are usually required to be deposited in public repositories upon publication. Such repositories have the enormous potential to provide a comprehensive view of how different experimental conditions lead to expression changes, by comparing gene expression across all possible measured conditions. Unfortunately, this task is greatly impaired by differences among experimental platforms that make direct comparisons difficult. In this paper, we present the Vitis Expression Studies Platform Using COLOMBOS Compendia Instances (VESPUCCI), a gene expression compendium for grapevine which was built by adapting an approach originally developed for bacteria, and show how it can be used to investigate complex gene expression patterns. We integrated nearly all publicly available microarray and RNA-Seq expression data: 1608 gene expression samples from 10 different technological platforms. Each sample has been manually annotated using a controlled vocabulary developed ad hoc to ensure both human readability and computational tractability. Expression data in the compendium can be visually explored using several tools provided by the web interface or can be programmatically accessed using the REST interface. VESPUCCI is freely accessible at http://vespucci.colombos.fmach.it. Frontiers Media S.A. 2016-05-10 /pmc/articles/PMC4862315/ /pubmed/27242836 http://dx.doi.org/10.3389/fpls.2016.00633 Text en Copyright © 2016 Moretto, Sonego, Pilati, Malacarne, Costantini, Grzeskowiak, Bagagli, Grando, Moser and Engelen. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Moretto, Marco
Sonego, Paolo
Pilati, Stefania
Malacarne, Giulia
Costantini, Laura
Grzeskowiak, Lukasz
Bagagli, Giorgia
Grando, Maria Stella
Moser, Claudio
Engelen, Kristof
VESPUCCI: Exploring Patterns of Gene Expression in Grapevine
title VESPUCCI: Exploring Patterns of Gene Expression in Grapevine
title_full VESPUCCI: Exploring Patterns of Gene Expression in Grapevine
title_fullStr VESPUCCI: Exploring Patterns of Gene Expression in Grapevine
title_full_unstemmed VESPUCCI: Exploring Patterns of Gene Expression in Grapevine
title_short VESPUCCI: Exploring Patterns of Gene Expression in Grapevine
title_sort vespucci: exploring patterns of gene expression in grapevine
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4862315/
https://www.ncbi.nlm.nih.gov/pubmed/27242836
http://dx.doi.org/10.3389/fpls.2016.00633
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